Modulation classification (MC) plays an important role in numerous military, civilian and commercial applications such as electronic warfare, spectrum surveillance, software defined radio (SDR) and cognitive radios. For example, SDRs that can detect, communicate or jam a variety of communication standards require automatic recognition of the signal modulation employed when no prior knowledge of the incoming signal is available to perform their function. Generally, MC is challenging task in a non-cooperative environment, where various disturbing factors such as multipath propagation, frequency-selectivity and time-varying nature of the channel exists.
Typically, two classes of MC algorithms exist, likelihood-based (LB) and feature-based (FB) methods. LB algorithms include a likelihood function performed on the received signal, and a decision algorithm performed by comparing a likelihood ratio against a threshold. Solutions offered by LB algorithms offer a high level of classification performance. However, the solutions suffer from implementational complexity, and sensitivity to model mismatches such as frequency offset, thereby making LB algorithms unpreferrable in realistic applications. On the other hand, the FB methods are more suitable for practical systems as they are simpler to implement and more robust to model mismatches. Although the FB methods are not optimal, with appropriate design a near-optimal performance is achievable.
New generation communication systems are increasingly deploying Multiple-input multiple-output (MIMO) antenna systems due to increased data rates and robust communications in multipath fading channels. While several techniques have been deployed for MC of signals in Single-Input Single-Output (SISO) systems, only studies have considered MC algorithms for MIMO systems in fading channels. For example, the following prior art are provided for their supportive teachings and are all incorporated by reference. Prior art document, H.-C. Wu, M. Saquib, and Z. Yun, “Novel automatic modulation classification using cumulant features for communications via multipath channels,” IEEE Trans. Wireless Communication, vol. 7, pp. 3098-3105, Aug. 2008 (https://ieeexplore.ieee.org/document/4600222/), discloses the use of fourth-order cumulant estimators for automatic modulation classification (AMC) of BPSK and QPSK signals over an additive white Gaussian noise channel. Further, the prior art, includes a nearly minimum-variance estimator leading to robust AMC features in a wide variety of signal-to-noise ratios and without having a priori channel information. However, the disclosed prior art is applicable to SISO systems only and cannot be deployed in communications involving MIMO antenna systems.
Another prior art document, V. D. Orlic and M. L. Dukic, “Automatic modulation classification algorithm using higher-order cumulants under real-world channel conditions,” IEEE Commun. Lett, vol. 13, pp. 917-919, December 2009 (https://www.researchgate.net/publication/220303345_Automatic_Modulation_Classificati on_Algorithm_Using_Higher-Order_Cumulants_Under_Real-World_Channel_Conditions), describes use of an AMC algorithm for use in multipath fading channels, based on normalized sixth-order cumulants as MC features. The prior art MC algorithm achieve much better classification accuracy in distinguishing BPSK from complex-valued modulation techniques. However, disclosed prior art cannot be used in MIMO systems.
Another prior art document, M. Marey and O. A. Dobre, “Blind modulation classification algorithm for single and multiple-antenna systems over frequency-selective channels,” IEEE Signal Process. Lett., vol. 21, pp. 1098-1102, September 2014, describes a blind modulation classification (MC) algorithm applicable to SISO and MIMO systems operating over frequency-selective channels. A correlation-based approach is proposed in the disclosed prior art, where functions of received signals for certain modulation formats exhibit peaks at a set of time lags, a result which is exploited as a discriminating feature. However, the disclosed prior art technique suffers from high sensitivity to frequency offset and requires a long observation interval to achieve desirable performance.
Another, prior art document U.S. Pat. No. 6,934,342 B1 “Automatic Modulation Type Discrimination Apparatus and Automatic Modulation Type Discrimination Method Capable of Discriminating Plural Kinds of Modulation Types”, discloses an AMC technique for detecting the modulation of a received signal. The disclosed technique involves, extraction of a symbol clock and an extension of a signal symbol from the received signal for extracting a characteristic of its amplitude distribution. Based on the extracted characteristic of the amplitude distribution, it is determined whether the reception signal is a 16 QAM signal and an M-ary QAM signal of multi-level exceeding 16-levels or any other signal. Several backtracking and preprocessing of the received signal involved in the disclosed process makes the process time consuming and computationally complex.
There is a need for an alternate method and system for detecting MC in multipath fading channels for both SISO and MIMO systems. Further, the alternate method and system must be computationally less complex and less time consuming. Accordingly, an alternate method and system for MC of signals in communication systems is proposed.